Parallel opsin switches in multiple cone types of the starry flounder retina: tuning visual pigment composition for a demersal life style
Bibliographic record
Abstract
Abstract Variable expression of visual pigment proteins (opsins) in cone photoreceptors of the vertebrate retina is a primary determinant of vision plasticity. Switches in opsin expression or variable co-expression of opsins within differentiated cones have been documented for a few rodents and fishes, but the extent of photoreceptor types affected and potential functional significance are largely unknown. Here, we show that both single and double cones in the retina of a flatfish, the starry flounder (Platichthys stellatus), undergo visual pigment changes through opsin switches or variable opsin co-expression. As the post-metamorphic juvenile (i.e., the young asymmetric flatfish with both eyes on one side of the body) grows from ~5 g to ~196 g, some single cones and one member of unequal double cones switched from a visual pigment with maximum wavelength of absorbance, λmax, at shorter wavelengths (437 nm and 527 nm) to one with longer λmax (456 nm and 545 nm, respectively) whereas other cones had intermediate visual pigments (λmax at 445 nm or 536 nm) suggesting co-expression of two opsins. The shift toward longer wavelength absorbing visual pigments was in line with maximizing sensitivity to the restricted light spectrum at greater depths and achromatic detection of overhead targets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".